dsifry/metaswarm

297 stars · Last commit 2026-05-16

A self-improving multi-agent orchestration framework for Claude Code, Gemini CLI, and Codex CLI — 18 agents, 13 skills, 15 commands, TDD enforcement, quality gates, spec-driven development

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# metaswarm

A self-improving multi-agent orchestration framework for [Claude Code](https://docs.anthropic.com/en/docs/claude-code), Gemini CLI, and Codex CLI. Coordinate 18 specialized AI agents and 13 orchestration skills through a complete software development lifecycle, from issue to merged PR, with recursive orchestration, parallel review gates, and a git-native knowledge base.

## What Is This?

metaswarm is an extraction of a production-tested agentic orchestration system. It has been proven in the field writing production-level code with 100% test coverage, mandatory TDD, multi-reviewed spec-driven development, and SDLC best practices across hundreds of PRs. It provides:

- **18 specialized agent personas** (Researcher, Architect, Coder, Security Auditor, PR Shepherd, etc.)
- **A structured 9-phase workflow**: Research → Plan → Design Review Gate → Work Unit Decomposition → Orchestrated Execution → Final Review → PR Creation → PR Shepherd → Closure & Learning
- **4-Phase Orchestrated Execution Loop**: Each work unit runs through IMPLEMENT → VALIDATE → ADVERSARIAL REVIEW → COMMIT. The orchestrator validates independently (never trusts subagent self-reports), and adversarial reviewers check DoD compliance with file:line evidence
- **Parallel Design Review Gate**: 5 specialist agents (PM, Architect, Designer, Security, CTO) review in parallel with a 3-iteration cap before human escalation
- **Recursive orchestration**: Swarm Coordinators spawn Issue Orchestrators, which spawn sub-orchestrators for complex epics (swarm of swarms)
- **Git-native task tracking**: Uses [BEADS](https://github.com/steveyegge/beads) (`bd` CLI) for issue/task management, dependencies, and knowledge priming
- **Knowledge base**: JSONL-based fact store for patterns, gotchas, decisions, and anti-patterns — agents prime from this before every task
- **Quality rubrics**: Standardized review criteria for code, architecture, security, testing, planning, and adversarial spec compliance
- **External AI tool delegation**: Optionally delegate implementation and review tasks to OpenAI Codex CLI and Google Gemini CLI for cost savings and cross-model adversarial review
- **Visual review**: Playwright-based screenshot capture for reviewing web UIs, presentations, and rendered pages
- **PR lifecycle automation**: Autonomous CI monitoring, review comment handling, and thread resolution
- **Workflow enforcement**: Mandatory quality gate intercepts at every handoff point — agents cannot skip design review, plan review, or knowledge capture

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